Reuse in Intelligent Systems
The book is based on the best papers of IEEE IRI 2018 and IEEE FMI 2018, Salt Lake City, July, 2018. They have been enhanced and modified suitably for publication. The book comprises recent works covering several aspects of reuse in intelligent systems–including Scientific Theory and Technology-Base...
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creator | Lydia Bouzar-Benlabiod Stuart H Rubin |
description | The book is based on the best papers of IEEE IRI 2018 and IEEE FMI 2018, Salt Lake City, July, 2018. They have been enhanced and modified suitably for publication. The book comprises recent works covering several aspects of reuse in intelligent systems–including Scientific Theory and Technology-Based Applications. New data analytic algorithms, technologies, and tools are sought to be able to manage, integrate, and utilize large amounts of data despite hardware, software, and/or bandwidth constraints; to construct models yielding important data insights, and to create visualizations to aid in presenting and understanding the data. Furthermore, it addresses the representation, cleansing, generalization, validation, and reasoning strategies for the scientifically-sound and cost-effective advancement of all kinds of intelligent systems–including all software and hardware aspects. The book addresses problems such as, how to optimally select the information/data sets for reuse and how to optimize the integration of existing information/knowledge with new, developing information/knowledge sources! |
doi_str_mv | 10.1201/9781003034971 |
format | Book |
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They have been enhanced and modified suitably for publication. The book comprises recent works covering several aspects of reuse in intelligent systems–including Scientific Theory and Technology-Based Applications. New data analytic algorithms, technologies, and tools are sought to be able to manage, integrate, and utilize large amounts of data despite hardware, software, and/or bandwidth constraints; to construct models yielding important data insights, and to create visualizations to aid in presenting and understanding the data. Furthermore, it addresses the representation, cleansing, generalization, validation, and reasoning strategies for the scientifically-sound and cost-effective advancement of all kinds of intelligent systems–including all software and hardware aspects. The book addresses problems such as, how to optimally select the information/data sets for reuse and how to optimize the integration of existing information/knowledge with new, developing information/knowledge sources!</description><subject>Abnormal Behavior Patterns</subject><subject>Artificial Intelligence</subject><subject>Big Data</subject><subject>Bioinformatics</subject><subject>Class Imbalance</subject><subject>Computer software</subject><subject>COMPUTERSCIENCEnetBASE</subject><subject>Congresses</subject><subject>Data mining</subject><subject>Data Sampling</subject><subject>Gene Selection</subject><subject>Holt-Winters</subject><subject>Human Computer Intelligence</subject><subject>Industrial applications</subject><subject>INFORMATIONSCIENCEnetBASE</subject><subject>ITECHnetBASE</subject><subject>Logs Behavior</subject><subject>Long Short-Term Memory</subject><subject>Machine Learning</subject><subject>Medicare Fraud detection</subject><subject>Noise Injection</subject><subject>Random Forest</subject><subject>Random Undersampling</subject><subject>Reusability</subject><subject>Root Mean Square Error</subject><subject>SCI-TECHnetBASE</subject><subject>Sequence of Events</subject><subject>Special computer methods</subject><subject>STMnetBASE</subject><subject>Subset Evaluation</subject><subject>Wrapper Feature Selection</subject><isbn>1000089290</isbn><isbn>9781000089295</isbn><isbn>0367510073</isbn><isbn>9780367510077</isbn><isbn>9780367473389</isbn><isbn>0367473380</isbn><isbn>1003034977</isbn><isbn>1000089290</isbn><isbn>9781003034971</isbn><isbn>9781000089639</isbn><isbn>9781000089295</isbn><isbn>9781000089448</isbn><isbn>1000089444</isbn><isbn>1000089630</isbn><fulltext>true</fulltext><rsrctype>book</rsrctype><creationdate>2020</creationdate><recordtype>book</recordtype><sourceid>I4C</sourceid><recordid>eNqNkUtPAjEUhWuMRkWW7lwQN8YFevuYabtUgo-ExMTHuikzHWgoLbYDhH_vwBCjO1ftSb5zes8tQhcYbjEBfCe5wAAUKJMcH6CzH8EPdwJASCLhuBGY5VkmJdAT1E3JjoGBxAxTfIou38wymZ71vRdfG-fsxPi6975JtZmnc3RUaZdMd3920Ofj8GPw3B-9Pr0M7kd9TQjNRF8QXPBcsrxgpASem5JTIQtMBdPbO-iK0nGGweCME0FAVJUsRWVoaQozph100-bqNDPrNA2uTmrlzDiEWVJt0bZO1rDXLbuI4WtpUq12WNGMHbVTw4dBjhkjBBqStaT1VYhzvQ7RlarWGxdiFbUvbPr9wH6TjW34PxsGtf2Iv3a1MjHZ4EmTc9XmFDppZ71V8-DDJOrFNCnGM8K4pN8CHIR5</recordid><startdate>2020</startdate><enddate>2020</enddate><creator>Lydia Bouzar-Benlabiod</creator><creator>Stuart H Rubin</creator><general>CRC Press</general><general>Taylor & Francis Group</general><scope>I4C</scope></search><sort><creationdate>2020</creationdate><title>Reuse in Intelligent Systems</title><author>Lydia Bouzar-Benlabiod ; 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subjects | Abnormal Behavior Patterns Artificial Intelligence Big Data Bioinformatics Class Imbalance Computer software COMPUTERSCIENCEnetBASE Congresses Data mining Data Sampling Gene Selection Holt-Winters Human Computer Intelligence Industrial applications INFORMATIONSCIENCEnetBASE ITECHnetBASE Logs Behavior Long Short-Term Memory Machine Learning Medicare Fraud detection Noise Injection Random Forest Random Undersampling Reusability Root Mean Square Error SCI-TECHnetBASE Sequence of Events Special computer methods STMnetBASE Subset Evaluation Wrapper Feature Selection |
title | Reuse in Intelligent Systems |
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